Observer-Based Event-Triggered Adaptive Decentralized Fuzzy Control for Nonlinear Large-Scale Systems

Abstract

For a class of large-scale nonlinear systems in nonstrict-feedback structure with immeasurable states, an adaptive decentralized fuzzy control strategy on the basis of event-triggered mechanism is investigated in this paper. Fuzzy logic systems are implemented to construct an observer, which approximates the unknown nonlinear function in the controller. In light of backstepping control technique and event-triggered mechanism, a decentralized adaptive fuzzy control approach is proposed to compensate for the effects of actuator faults. When the triggering condition is satisfied, the communication burden can be reduced. Moreover, the whole signals of the closed-loop system are semiglobally uniformly ultimately bounded and Zeno behavior can be successfully excluded. Furthermore, the outputs of subsystems can track the desired reference signals. Finally, some simulation results are utilized to testify the effectiveness of the proposed control scheme.